Tim Schumacher

Training Neural Networks: Advanced Learning Algorithms

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Training Neural Networks: Implementing the Learning Process

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Building Neural Networks: Artificial Neural Networks Using Frameworks

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Building Neural Networks: Development Principles

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Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms

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Getting Started with Neural Networks: Biological & Artificial Neural Networks

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ML Programmer

TRACK

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®

Final Exam: ML Programmer

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Linear Models & Gradient Descent: Managing Linear Models

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Linear Models & Gradient Descent: Gradient Descent and Regularization

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Building ML Training Sets: Preprocessing Datasets for Classification

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Building ML Training Sets: Introduction

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Building ML Training Sets: Preprocessing Datasets for Linear Regression

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Math for Data Science & Machine Learning

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Reinforcement Learning: Tools & Frameworks

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Reinforcement Learning: Essentials

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